75 lines
2.0 KiB
C++
75 lines
2.0 KiB
C++
#include "gtl_math_kurt.h"
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namespace gtl
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{
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namespace math
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{
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kurt::kurt(gtl::analog_data *data)
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: analog_value(data)
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, _sum(0)
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, _mean(0)
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, _full_ring(false)
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, _prev_data_ptr(-1)
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{
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_name = "kurtosis";
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}
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void kurt::before_copying_data(std::vector<qreal>::iterator begin, std::vector<qreal>::iterator end)
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{
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_sum -= std::accumulate(begin, end, 0.0);
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}
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void kurt::after_copying_data(std::vector<qreal>::iterator begin, std::vector<qreal>::iterator end)
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{
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_sum += std::accumulate(begin, end, 0.0);
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_mean = _sum/_data.size();
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}
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void kurt::data_changed()
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{
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analog_value::data_changed();
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if(_prev_data_ptr >= _data_ptr && !_full_ring) _full_ring = true;
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else _prev_data_ptr = _data_ptr;
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int n = _full_ring ? _data.size() : _data_ptr;
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if(n > 3)
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{
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qreal variance = 0.;
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for(int i=0; i<n; i++)
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if(_full_ring)
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variance += pow((_data[(_data_ptr + i) % _data.size() ] - _mean), 2);
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else
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variance += pow((_data[i] - _mean), 2);
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variance /= n;
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qreal sigma = 0;
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for(int i=0; i<n; i++)
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if(_full_ring)
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sigma += pow((_data[(_data_ptr + i) % _data.size() ] - _mean), 4);
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else
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sigma += pow((_data[i] - _mean), 4);
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sigma /= n;
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qreal k1 = (qreal)(n*n - 1) / (qreal)((n-2)*(n-3));
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qreal k2 = (qreal)((6. / (n + 1.)) - 3.);
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_value = k1*(sigma/pow(variance,2) + k2);
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}
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else
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{
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_value = 0;
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return;
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}
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emit value_changed();
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}
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}
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}
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